The most appropriate technique for a binary outcome prediction in the predictive analytics maturity phase is B. Logistic Regression.

Here's why:

A. Linear Regression: This is typically used for predicting a continuous outcome variable (i.e., a variable that can have any number of values, not just two).

B. Logistic Regression: This is the correct answer. Logistic regression is used when the dependent variable is binary (i.e., it only has two possible outcomes).

C. Time Series Analysis: This is used for analyzing data that is collected over time and where the order of the data points is important. It's not typically used for binary outcome prediction.

D. Multinomial Regression: This is used when the dependent variable is categorical and has more than two categories. It's not used for binary outcome prediction.

Question

The most appropriate technique for a binary outcome prediction in the predictive analytics maturity phase is B. Logistic Regression.

Here's why:

A. Linear Regression: This is typically used for predicting a continuous outcome variable (i.e., a variable that can have any number of values, not just two).

B. Logistic Regression: This is the correct answer. Logistic regression is used when the dependent variable is binary (i.e., it only has two possible outcomes).

C. Time Series Analysis: This is used for analyzing data that is collected over time and where the order of the data points is important. It's not typically used for binary outcome prediction.

D. Multinomial Regression: This is used when the dependent variable is categorical and has more than two categories. It's not used for binary outcome prediction.

Knowee AI · Accepted Answer

The most appropriate technique for a binary outcome prediction in the predictive analytics maturity phase is B. Logistic Regression.

Here's why:

A. Linear Regression: This is typically used for predicting a continuous outcome variable (i.e., a variable that can have any number of values, not just two).

B. Logistic Regression: This is the correct answer. Logistic regression is used when the dependent variable is binary (i.e., it only has two possible outcomes).

C. Time Series Analysis: This is used for analyzing data that is collected over time and where the order of the data points is important. It's not typically used for binary outcome prediction.

D. Multinomial Regression: This is used when the dependent variable is categorical and has more than two categories. It's not used for binary outcome prediction.

For a binary outcome prediction in the predictive analytics maturity phase, which of the following technique is most appropriate? A. Linear Regression B. Logistic Regression C. Time Series Analysis D. Multinomial Regression

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